CN112113319B

CN112113319B - Air conditioner load adjusting system and air conditioner load adjusting method

Info

Publication number: CN112113319B
Application number: CN201910604616.2A
Authority: CN
Inventors: 杨盛闵; 何承怿; 程文彦; 杜德美
Original assignee: Chicony Power Technology Co Ltd
Current assignee: Chicony Power Technology Co Ltd
Priority date: 2019-06-20
Filing date: 2019-07-05
Publication date: 2021-08-03
Anticipated expiration: 2039-07-05
Also published as: TW202100915A; CN112113319A; TWI699500B

Abstract

The invention discloses an air conditioning load adjusting system and an air conditioning load adjusting method, wherein the air conditioning load adjusting system is arranged in a building with air conditioning equipment and comprises the following components: the air-conditioning load prediction unit is used for calculating the predicted load amount of the air-conditioning equipment in a future time interval according to the data of the past time interval; the indoor temperature and humidity sensing module senses the temperature and humidity of the building at the first time; the wind speed sensing module senses the wind speed of the air conditioning equipment at a first time; the comfort degree prediction module is used for calculating the comfort degree of the air conditioning equipment at the second time according to the temperature, the humidity and the wind speed; and the energy management platform controls the central monitoring computer to generate a temperature set value and a wind speed set value of the air conditioning equipment according to the comfort level. The central monitoring computer compares the predicted load with the actual load of the air conditioning equipment when the air conditioning equipment is in operation, and corrects the temperature set value and the wind speed set value according to the comparison result. The invention can achieve the purposes of saving energy and reducing the electricity consumption in the peak time period.

Description

Air conditioner load adjusting system and air conditioner load adjusting method

Technical Field

The present invention relates to the field of air conditioners, and more particularly, to an adjustment system and an adjustment method for adjusting air conditioning load.

Background

Large air conditioning systems are usually configured with corresponding ice water hosts, which perform an ice making process during off-peak periods when the electricity charges are relatively low, and the air conditioning systems can perform heat exchange using pre-made ice blocks during off-peak periods when the electricity charges are relatively high, thereby reducing the electricity cost required by the air conditioning systems.

The ice making process of an ice water host machine will typically have a fixed amount of ice stored. However, internal factors (such as the number of people or the content of activities) and external factors (such as temperature or humidity) that affect the comfort level in a building are different every day, and if the air conditioning system is controlled to maintain a constant comfort level in the room during each period of the day, the problem of insufficient storage of ice may arise.

When the ice storage capacity is insufficient (namely the actual load capacity of the air conditioning system exceeds the predicted load capacity), the air conditioning system needs to start the ice water host in real time to perform the ice making process again. However, the ice making process may consume a high electricity charge during the peak period, and the additional electricity may cause the overall electricity usage of the air conditioning system to exceed the contract capacity.

Moreover, when the indoor environment changes drastically (for example, suddenly becomes hot), the air conditioning system needs to drive the ice water main unit to operate drastically to improve the environment quickly, so that the ice water main unit exceeds the optimal efficiency range of 60% -80%, which also causes the increase of the overall power consumption of the air conditioning system.

In view of the above, it is an important research topic in the art to predict the load of the air conditioning system and optimize the operation of the air conditioning system accordingly.

Disclosure of Invention

The invention aims to provide an air conditioner load adjusting system and an air conditioner load adjusting method, which can keep the indoor space within a certain comfort level range, and can achieve the optimal control of air conditioning equipment according to the prediction of the air conditioner load so as to achieve the purposes of saving energy and reducing the electricity consumption in the peak time period.

In order to achieve the above object, the present invention provides an air conditioning load adjusting system applied in a building, comprising:

a central monitoring computer;

an air conditioner load prediction unit which is in communication connection with the central monitoring computer through an energy management platform, predicts a predicted load capacity of an air conditioner in a future time interval according to a plurality of data obtained in a past time interval, and provides the predicted load capacity to the energy management platform;

the indoor temperature and humidity sensing module senses and outputs a sensed temperature and a sensed humidity of the building at a first time;

the air speed sensing module senses and outputs an air conditioner air speed of the air conditioning equipment at the first time;

a comfort prediction module, which is in communication connection with the central monitoring computer through the energy management platform, calculates an indoor comfort default value required to be reached by the air conditioning equipment at a second time according to the sensed temperature, the sensed humidity and the air conditioning wind speed, and provides the indoor comfort default value to the energy management platform, wherein the second time is later than the first time, and the second time is within the future time interval;

the energy management platform controls the central monitoring computer to generate a temperature set value and a wind speed set value of the air conditioning equipment according to the indoor comfort degree default value;

when the air conditioning equipment operates based on the temperature set value and the wind speed set value, the central monitoring computer corrects the temperature set value and the wind speed set value in real time according to a comparison result of the predicted load and an actual load of the air conditioning equipment.

As described above, the system further includes a black-ball temperature sensing module for sensing and outputting a radiation temperature of the building at the first time, and the comfort prediction module calculates the indoor comfort default value according to the sensed temperature, the sensed humidity, the air speed of the air conditioner and the radiation temperature.

As described above, the indoor comfort prediction module obtains a human activity meter and a clothing meter, and calculates the indoor comfort default value according to the sensed temperature, the sensed humidity, the air-conditioning wind speed, the radiation temperature, the human activity meter and the clothing meter.

As described above, the indoor comfort prediction module stores a plurality of human activity meters corresponding to different places, and reads the corresponding human activity meters according to the property of the building.

As described above, the indoor comfort prediction module stores a plurality of clothing meters corresponding to different climates, and reads the corresponding clothing meters according to the outdoor temperature of the building.

As described above, the indoor comfort prediction module stores a plurality of clothing meters corresponding to different climates, and reads the corresponding clothing meters according to the current season.

As described above, the energy management platform increases the default indoor comfort level that the air conditioner needs to reach at the second time when determining that the predicted load amount is higher than the actual load amount in a future period of time.

As described above, the central monitoring computer increases the temperature setting value and decreases the wind speed setting value according to the adjusted indoor comfort level default value.

As described above, when the energy management platform determines that the predicted load amount is lower than the actual load amount in a future period of time, the energy management platform decreases the default indoor comfort level value that the air conditioning device needs to reach at the second time.

As described above, the central monitoring computer lowers the temperature setting value and raises the wind speed setting value according to the lowered indoor comfort level default value.

As described above, wherein the air conditioning load prediction unit includes:

the air conditioning equipment scheduling management module outputs a scheduling parameter of the air conditioning equipment in the past time interval;

an indoor temperature setting module for outputting an indoor temperature setting condition of the building in the past time interval;

the building shell load acquisition module outputs a shell load factor of the building in the past time interval;

a weather forecast data acquisition module for outputting a weather forecast data of the future time interval; and

and the air conditioner load prediction module is used for calculating the predicted load according to the scheduling parameter, the indoor temperature setting condition, the shell load factor and the weather forecast data.

As described above, the weather forecast data includes an outside air temperature and a relative humidity of the future time interval.

As described above, the building shell load collection module calculates the shell load factor according to a building windowing frequency, a building window shading factor and at least one building orientation data of the building in the past time interval.

As described above, the air conditioning load prediction module calculates an outdoor enthalpy value according to the weather forecast data, calculates an indoor enthalpy value according to the indoor temperature setting condition, calculates an indoor/outdoor enthalpy difference value according to the outdoor enthalpy value and the indoor enthalpy value, calculates an outdoor air introducing load according to the scheduling parameter and the outdoor enthalpy value, and calculates the predicted load capacity according to the outdoor air introducing load, the indoor/outdoor enthalpy difference value, and the shell load factor.

In order to achieve the above object, the present invention provides an air conditioning load adjusting method applied to a building and controlling an air conditioning device in the building, and comprising the steps of:

a) predicting a predicted load capacity of the air conditioning equipment in a future time interval by an air conditioning load prediction unit according to a plurality of data obtained in a past time interval;

b) sensing a sensing temperature and a sensing humidity of the building at a first time through an indoor temperature and humidity sensing module;

c) sensing an air conditioning speed of the air conditioning equipment at the first time through an air speed sensing module;

d) calculating an indoor comfort level default value to be reached by the air conditioning equipment at a second time according to the sensed temperature, the sensed humidity and the air conditioning wind speed through a comfort level prediction module, wherein the second time is later than the first time, and the second time interval falls into the future time interval;

e) controlling a central monitoring computer to generate a temperature set value and a wind speed set value of the air conditioning equipment through an energy management platform according to the indoor comfort degree default value;

f) controlling the air conditioning equipment to operate based on the temperature set value and the wind speed set value; and

g) the central monitoring computer corrects the temperature set value and the wind speed set value in real time according to a comparison result of the predicted load amount and an actual load amount of the air conditioning equipment.

As mentioned above, the step d) further comprises a step d 1): sensing a radiation temperature of the building at the first time through a black ball temperature sensing module;

wherein, the step d) is to calculate the default value of the indoor comfort degree according to the sensed temperature, the sensed humidity, the air speed of the air conditioner and the radiation temperature.

As mentioned above, the step d) further comprises a step d 2): obtaining a human activity scale and a clothing scale;

wherein, the step d) is to calculate the default value of the indoor comfort level according to the sensed temperature, the sensed humidity, the air speed of the air conditioner, the radiation temperature, the human activity meter and the clothing meter.

As mentioned above, the indoor comfort prediction module stores a plurality of human activity meters corresponding to different locations, and the step d2) reads the corresponding human activity meter according to the property of the building.

As described above, the indoor comfort prediction module stores a plurality of clothing meters corresponding to different climates, and the step d2) reads the corresponding clothing meter according to the outdoor temperature of the building.

As described above, the indoor comfort prediction module stores a plurality of clothing meters corresponding to different climates, and the step d2) reads the corresponding clothing meter according to the current season.

As described above, wherein the step g) comprises the steps of:

g11) when the predicted load amount of the future period of time is judged to be higher than the actual load amount, the indoor comfort degree default value which is required to be reached by the air conditioning equipment at the second time is increased; and

g12) and increasing the temperature set value and reducing the wind speed set value according to the adjusted indoor comfort degree default value.

As described above, wherein the step g) comprises the steps of:

g21) when the predicted load amount of the future period of time is lower than the actual load amount, lowering the indoor comfort degree default value which is required to be reached by the air conditioning equipment at the second time; and

g22) and reducing the temperature set value and increasing the wind speed set value according to the reduced indoor comfort degree default value.

As mentioned above, wherein the step a) comprises the steps of:

a1) outputting a schedule parameter of the air conditioning equipment in the past time interval through an air conditioning equipment schedule management module;

a2) outputting an indoor temperature setting condition of the building in the past time interval through an indoor temperature setting module;

a3) outputting a shell load factor of the building in the past time interval through a building shell load acquisition module;

a4) outputting a weather forecast data of the future time interval through a weather forecast data acquisition module; and

a5) and calculating the predicted load amount through an air conditioner load prediction module according to the scheduling parameter, the indoor temperature setting condition, the shell load factor and the weather forecast data.

As described above, in the step a5), an outdoor enthalpy value is calculated according to the weather forecast data, an indoor enthalpy value is calculated according to the indoor temperature setting condition, an indoor/outdoor enthalpy difference value is calculated according to the outdoor enthalpy value and the indoor enthalpy value, an outdoor air introducing load is calculated according to the scheduling parameter and the outdoor enthalpy value, and the predicted load capacity is calculated according to the outdoor air introducing load, the indoor/outdoor enthalpy difference value and the shell load factor.

Compared with the prior art, the indoor comfort level (and the control parameter adopted for achieving the comfort level) required by the air conditioning equipment at the present stage is corrected in real time by predicting the load capacity of the air conditioning equipment for a period of time in the future, so that the optimal control of the air conditioning equipment can be effectively realized, and the purposes of saving energy and reducing peak power consumption are further achieved.

The invention is described in detail below with reference to the drawings and specific examples, but the invention is not limited thereto.

Drawings

FIG. 1 is a first embodiment of a block diagram of an air conditioning load leveling system according to the present invention;

FIG. 2 is a first embodiment of a schematic diagram of an air conditioning load prediction unit of the present invention;

fig. 3 is a schematic diagram of a first embodiment of an indoor comfort level calculating unit according to the present invention;

FIG. 4 is a flow chart of a method for adjusting air conditioning load according to a first embodiment of the present invention;

FIG. 5 is a first embodiment of a modified flow chart of the air conditioning apparatus of the present invention;

FIG. 6 is a second embodiment of a modified flow chart of the air conditioning apparatus of the present invention;

FIG. 7 is a flowchart of a predicted load calculation according to a first embodiment of the present invention;

FIG. 8 is a flowchart of a second embodiment of the predicted load calculation according to the present invention.

Wherein, the reference numbers:

1 … air conditioning load adjustment system;

11 … air conditioning load prediction unit;

111 … air conditioning system schedule management module;

112 … indoor temperature setting module;

113 … building envelope load acquisition module;

114 … weather forecast data acquisition module;

115 … air conditioning load prediction module;

12 … indoor comfort level calculating unit;

121 … indoor temperature and humidity sensing module;

122 … wind speed sensing module;

123 … black ball temperature sensing module;

124 … human activity scale;

125 … clothing scale;

126 … comfort prediction module;

13 … energy management platform;

14 … central monitoring computer;

15 … air conditioning equipment;

S10-S30 … adjustment step;

s300 to S308, S320 to S328 …;

and S100 to S108, and S1080 to S1090 ….

Detailed Description

A preferred embodiment of the present invention will be described in detail with reference to the accompanying drawings.

Referring to fig. 1, a first embodiment of a block diagram of an air conditioning load adjusting system according to the present invention is shown. The invention discloses an air conditioner load adjusting system (hereinafter referred to as adjusting system 1), wherein the adjusting system 1 mainly comprises an air conditioner load predicting unit 11, an indoor comfort degree calculating unit 12, an energy management platform 13, a central monitoring computer 14 and an air conditioner 15. The air conditioner 15 is mainly installed in a building (not shown), and performs heat exchange with ice cubes generated by an ice making process (ice making process step) executed by an ice water host (not shown) to improve indoor comfort of the building.

In one embodiment, the energy management platform 13 is connected to the air conditioning load prediction unit 11, the indoor comfort level calculation unit 12 and the central monitoring computer 14, and the central monitoring computer 14 is connected to the air conditioning equipment 15 through a wired or wireless connection. Moreover, the central monitoring computer 14 can monitor the operation (such as the operation time, the set temperature, the fan speed, etc.) of the air conditioner 15, and can adjust the operation mode of the air conditioner 15 according to the set parameters such as the temperature, the humidity, etc.

In an embodiment of the present invention, the air conditioning load prediction unit 11 may predict a load capacity (hereinafter referred to as a predicted load capacity) of the air conditioning equipment 15 for a future period of time (e.g., one day) according to the collected data, and provide the predicted load capacity to the energy management platform 13. The energy management platform 13 may generate a control signal for controlling the central monitoring computer 14 according to the predicted load amount, and the central monitoring computer 14 may control the ice water host of the air conditioner 15 to execute an ice storage procedure (ice storage process step) according to the control signal (for example, the ice storage procedure may be executed in an off-peak period), so that the ice water host has an ice storage amount that can meet the predicted load amount after the ice storage procedure is completed. If the cumulative load of the air conditioner 15 during the day does not exceed the predicted load, the problem of insufficient ice storage will not occur.

One of the key points of the present invention is that the air conditioning load prediction unit 11 is configured to obtain a plurality of data generated during a past time interval at a location where the air conditioning equipment 15 is located (i.e., the building), and predict a load amount (hereinafter, referred to as a predicted load amount) that the air conditioning equipment 15 may generate during a future time interval according to the data. The air conditioning load prediction unit 11 provides the calculated predicted load amount to the energy management platform 13, and the energy management platform 13 may use the predicted load amount as one of the parameters for performing the optimal control on the air conditioning equipment 15.

In this embodiment, the past time interval refers to a period of time earlier than the current time, for example, yesterday's working time or today's working time (finished). The future time interval refers to a period of time later than the current time, such as the work hours of tomorrow or 24 hours from the current time, and is not limited.

Fig. 2 is a schematic diagram of an air conditioning load prediction unit according to a first embodiment of the present invention. The air conditioning load prediction unit 11 may be a physical unit (e.g., implemented by a processor) or a virtual unit (e.g., implemented by software), and as shown in fig. 2, may include an air conditioning system schedule management module 111, an indoor temperature setting module 112, a building shell load collection module 113, a weather forecast data collection module 114, and an air conditioning load prediction module 115 according to each execution function of the air conditioning load prediction unit 11.

In this embodiment, the air conditioning System schedule management module 111 may be in communication connection with the air conditioning equipment 15, the central monitoring computer 14, or a Building Automation System (BA System, not shown) to obtain the schedule parameters of the air conditioning equipment 15 in the past time interval. The indoor temperature setting module 112 may be communicatively connected to the air conditioner 15, the central monitoring computer 14, or one or more sensors (not shown) disposed inside or outside the building to obtain a set of indoor temperature setting conditions of the building during a past time interval. The building envelope load acquisition module 113 may be communicatively coupled to the central monitoring computer 14 or the building automation system to obtain envelope load factors for the building over a past time interval.

The weather forecast data collecting module 114 may be in communication with the central monitoring computer 14 or the building automation system, or may be in communication with a weather forecasting platform (e.g., a central meteorological office website) via a network to obtain weather forecast data (e.g., hourly outside air temperature, hourly relative humidity, etc.) for the future time interval. In one embodiment, the weather forecast data collecting module 114 mainly obtains the weather forecast data of the future time interval where the air conditioner 15 is located from a weather forecast platform, but is not limited thereto.

The air conditioning load prediction module 115 can obtain the data of the schedule parameter, the indoor temperature setting condition, the shell load factor, the weather forecast data and the like from the air conditioning system schedule management module 111, the indoor temperature setting module 112, the building shell load collection module 113 and the weather forecast data collection module 114, respectively, predict the air conditioning load that the air conditioning equipment 15 may need to bear in the future time interval by using the corresponding algorithm, and generate a predicted load amount. In this way, the adjusting system 1 of the present invention can optimally control the air conditioner 15 according to the predicted load.

Another key point of the present invention is that the adjusting system 1 can calculate the default indoor comfort level required by the air conditioner 15 at the second time according to the current situation through the indoor comfort level calculating unit 12, whereby the energy management platform 13 can adjust the operation of the air conditioner 15 according to the default indoor comfort level, so that the indoor environment of the building can be maintained within a certain comfort level range. In this embodiment, the second time is later than the current time (hereinafter referred to as the first time), and may be, for example, ten minutes later, one hour later, three hours later, and the like, without limitation.

It should be noted that the second time in this embodiment refers to a time point within the aforementioned future time interval. For example, if the future time interval is 24 hours into the future, the second time may be, for example, three hours later from now on. However, the above is only one specific implementation example of the present invention, and the present invention is not limited thereto.

Please refer to fig. 3, which is a schematic diagram of a first embodiment of an indoor comfort level calculating unit according to the present invention. In an embodiment, the indoor comfort level calculating unit 12 at least includes an indoor temperature and humidity sensing module 121, an air speed sensing module 122 and a comfort level predicting module 126.

In this embodiment, the indoor temperature and humidity sensing module 121 may sense a temperature and a humidity (hereinafter referred to as a sensed temperature and a sensed humidity) of a building at a first time (e.g., at present), and output the sensed temperature and the sensed humidity to the comfort prediction module 126. The wind speed sensing module 122 may sense the air conditioning wind speed of the air conditioning equipment 15 at the first time, and output the air conditioning wind speed to the comfort prediction module 126.

The comfort prediction module 126 is in communication connection with the central monitoring computer 14 via the energy management platform 13, and can calculate the indoor comfort default value that the air conditioning equipment 15 needs to reach at the second time according to the sensed temperature, the sensed humidity and the air conditioning wind speed. Also, the comfort prediction module 126 may provide the calculated indoor comfort default to the energy management platform 13 for optimal control of the air conditioning device 15 by the energy management platform 13.

In another embodiment, the indoor comfort level calculating unit 12 may further include a black ball temperature sensing module 123. The black ball temperature sensing module 123 is disposed in the building, and is configured to sense a radiation temperature of the building at the first time. The black ball temperature sensing module 123 outputs the sensed radiation temperature to the comfort prediction module 126. In this embodiment, the comfort prediction module 126 may calculate the indoor comfort default value according to the sensed temperature, the sensed humidity, the air-conditioning wind speed, and the radiation temperature. Because the radiation temperature inside the building is considered in the embodiment, the comfort degree can be more accurately predicted.

In another embodiment, the indoor comfort level calculating unit 12 further includes a human activity meter 124 and a clothing meter 125. The physical activity meter 124 records an activity index corresponding to activities in a particular location (e.g., an office), and the clothing meter 125 records a clothing index corresponding to indoor personnel wearing a particular garment (e.g., a suit or suit).

In this embodiment, the comfort prediction module 126 may read the human activity meter 124 and the clothing meter 125 to obtain the corresponding activity index and clothing index, and calculate the indoor comfort default value according to the sensed temperature, the sensed humidity, the air speed of the air conditioner, the radiation temperature, the human activity meter and the clothing meter. Because the activity and the clothing amount of the personnel in the building are simultaneously considered in the embodiment, the comfort degree can be more accurately predicted.

As described above, the indoor comfort level calculation unit 12 may calculate and generate an indoor comfort level default value through the comfort level prediction module 126, and provide the indoor comfort level default value to the energy management platform 13. In this embodiment, the energy management platform 13 may control the central monitoring computer 14 to generate a temperature setting value and a wind speed setting value of the air conditioning equipment 15 according to the indoor comfort level default value. Specifically, the air conditioner 15 adjusts the operation mode according to the temperature setting value and the wind speed setting value generated by the central monitoring computer 14, so that the indoor space of the building can reach the indoor comfort level default value before a predetermined time (i.e., the second time).

In this embodiment, the temperature set value is an indoor temperature (for example, 22 degrees or 24 degrees) to be maintained by the air conditioner 15, and the wind speed set value is a fan rotation speed (for example, weak wind or strong wind) to be used by the air conditioner 15.

Since the indoor and outdoor environmental factors are different every day, the load required by the air conditioner 15 is different when the indoor environment is set to the indoor comfort default value by the operation of the air conditioner 15.

One of the technical features of the present invention is that the central monitoring computer 14 can continuously monitor the actual load capacity of the air conditioner 15 when the air conditioner 15 is operated based on the temperature setting value and the wind speed setting value, that is, the actual load capacity of the air conditioner 15, which is generated when the air conditioner 15 is operated under the current environmental factors by using the temperature setting value and the wind speed setting value to make the indoor environment reach the indoor comfort level default value. The central monitoring computer 14 compares the predicted load amount with the current actual load amount, and corrects the current temperature setting value and the current wind speed setting value of the air conditioning equipment 15 in real time according to the comparison result of the predicted load amount and the actual load amount.

Specifically, the predicted load amount is a total load amount that may be required to be borne in the future time interval calculated by executing the prediction algorithm, and the actual load amount is a load amount generated by the current operation of the air conditioner 15. When the predicted load capacity at a non-point time (for example, after three hours) is higher than the actual load capacity at the current time, it means that the load capacity of the air conditioning equipment 15 is likely to be greatly increased, so the central monitoring computer 14 adjusts the operation mode of the air conditioning equipment 15 according to the above program to reduce the load capacity of the air conditioning equipment 15 at the next time in advance, thereby reducing the total power consumption of the air conditioning equipment 15 and achieving the purpose of saving energy. In addition, by correcting the temperature set value and the wind speed set value of the air conditioning equipment 15 in advance, the ice storage capacity of the ice water main machine of the air conditioning equipment 15 can be prevented from being unused, and the ice water main machine can be started slowly to maintain the optimal operation efficiency of 60-80%.

Fig. 4 is a flowchart illustrating a method for adjusting an air conditioning load according to a first embodiment of the present invention. The invention also discloses an air conditioner load adjusting method (hereinafter referred to as an adjusting method), which is applied to the adjusting system 1 shown in fig. 1. In particular, the regulation system 1 controls the operation of the air conditioning plant 15 in the building by means of the regulation method of the invention.

As shown in fig. 4, first, the air conditioning load prediction unit 11 of the adjustment system 1 predicts a predicted load amount that the air conditioning equipment 15 may be burdened in a future time interval (for example, tomorrow 'S working hours) from a plurality of data obtained in a past time interval (for example, yesterday' S working hours) (step S10). As described above, the plurality of data may be, for example, without limitation, scheduling parameters of the air conditioner 15 in the past time zone, indoor temperature setting conditions of buildings in the past time zone, shell load factors of buildings in the past time zone, weather forecast data related to the future time zone acquired in the past time zone, and the like.

Next, the adjusting system 1 senses a sensed temperature and a sensed humidity of the building at a first time (e.g., at present) through the indoor temperature and humidity sensing module 121 (step S12), and senses an air conditioning wind speed of the air conditioning equipment 15 at the first time through the wind speed sensing module 122 (step S14). Therefore, the comfort prediction module 126 of the adjustment system 1 can calculate the indoor comfort default value that the air conditioner 15 needs to reach at the second time (e.g., after one hour, after three hours, etc. from now on) according to the sensed temperature, the sensed humidity and the air conditioning wind speed (step S20). In this embodiment, the second time is later than the first time, and the second time falls within the future time interval.

It should be noted that, if the adjusting system 1 has the black-ball temperature sensing module 123 (disposed in the indoor space of the building), the adjusting system 1 can simultaneously sense the radiation temperature of the building at the first time through the black-ball temperature sensing module 123 (step S16). In this embodiment, the comfort prediction module 126 may calculate the indoor comfort default value according to the sensed temperature, the sensed humidity, the air-conditioning wind speed, and the radiation temperature.

In addition, if the adjustment system 1 further records the human activity meter 124 and the clothing meter 125 (for example, in the indoor comfort level calculation unit 12 or the comfort level prediction module 126), the adjustment system 1 may also obtain the human activity meter and the clothing meter at the same time (step S18). In this embodiment, the comfort prediction module 126 may calculate the indoor comfort default value according to the sensed temperature, the sensed humidity, the air-conditioning wind speed, the radiation temperature, the human activity meter, and the clothing meter.

Specifically, different locations may correspond to different activity indices (e.g., lower activity index for office, higher activity index for gym), and thus may be respectively adapted for different body activity scales 124. In one embodiment, the adjustment system 1 may store a plurality of physical activity meters 124 corresponding to different locations. In step S18, the adjusting system 1 can read the corresponding human activity meter 124 according to the property of the building, so as to make the calculated comfort level closer to the actual requirement.

In addition, different temperatures and climates may also correspond to different clothing indices (e.g., lower clothing index in summer and higher clothing index in winter), and thus may also be applied to different clothing scales 125, respectively. In one embodiment, the adjustment system 1 may store a plurality of clothing meters 125 corresponding to different climates. In step S18, the adjusting system 1 can read the corresponding clothing scale 125 according to the outdoor temperature of the building or the current season, thereby making the calculated comfort closer to the actual requirement.

The human activity meter 124 and the clothing meter 125 are commonly used in the art and will not be described herein.

Specifically, in one embodiment, the comfort prediction module 126 may calculate the indoor comfort level default of the air conditioner 15 according to the following calculation formula.

(1)

PMV＝(0.303e^-0.0036M+0.028)×(M-3.05×10^-3×(5773-6.99M-Pa)-0.42×(M-58.15)-1.7×10^-5×M×(5867-Pa)-0.0014×M×(34-Ta)-3.96×10^-8×Fcl×((Tcl+273)⁴-(Tr+273)⁴)-Tcl×Hc×(Tcl-Ta))；

(2)

Tcl＝(35.7-0.275×M+Icl×Fcl×(4.13×(1+0.01(Tr-20))+Hc×Ta))÷(1+Icl×Fcl×(4.13×(1+0.1Tr-20))+Hc)；

(3)

Hc＝12.1×Va^0.5×Va；

(4)

Fcl ═ 1+1.29 × Icl; when Ic1 is less than 0.0078;

(5)

fcl ═ 1.05+0.615 × Icl; when Icl is more than 0.0078;

(6)

Pa＝(RH÷100×e^{(18.6686-4030.18÷(Ta+235))}÷0.00750062)；

wherein, the PMV is a default value (-) of indoor comfort level, and M is human activity (W/M)²) Ta is air temperature (DEG C), Pa is water vapor partial pressure (Pa), RH is relative humidity (%), Fcl is clothes surface area coefficient (-), Icl is clothing thermal resistance (m)²x k/W), Tr is the average irradiation temperature (DEG C), Tcl is the surface temperature (DEG C) of the clothes, and Va is the average wind speed.

However, the above calculation formula is only a partial embodiment of the present invention, and the comfort level calculation program executed by the adjustment system 1 of the present invention is not limited to the above calculation formula.

After step S20, the energy management platform 13 of the adjusting system 1 generates a control command for controlling the central monitoring computer 14 according to the indoor comfort level default value (step S22), and the central monitoring computer 14 then generates a temperature setting value and a wind speed setting value for adjusting the operation mode of the air conditioning equipment 15 according to the control command (step S24). In the present invention, the adjusting system 1 first calculates the comfort level target to be achieved according to the actual parameters of the indoor environment of the building, and further calculates the air conditioning temperature and the air conditioning wind speed of the air conditioning equipment 15 required to achieve the comfort level target according to the comfort level target to be achieved.

After step S24, the central monitoring computer 14 connects the air conditioner 15 by wire or wireless connection, and controls the air conditioner 15 to operate based on the calculated temperature set value and the calculated wind speed set value (step S26). In this embodiment, if the air conditioner 15 operates based on the temperature setting value and the wind speed setting value, the indoor environment may reach the indoor comfort level default value when the second time arrives.

In the present invention, the adjusting system 1 may continuously monitor whether the operation of the air conditioner 15 is finished (step S28), i.e., whether the air conditioner 15 is turned off, through the central monitoring computer 14. When the air conditioner 15 is operating normally, the central monitoring computer 14 may monitor the air conditioner 15, calculate the current actual load capacity of the air conditioner 15, compare the predicted load capacity with the actual load capacity, and modify the temperature setting value and the wind speed setting value adopted by the air conditioner 15 in real time according to the comparison result (step S30). Before the operation of the air conditioner 15 is not completed, the process returns to step S26, and the central monitoring unit 14 controls the air conditioner 15 to operate at the corrected temperature setting value and the corrected wind speed setting value.

As described above, the main purpose of the present invention is to pre-adjust the load of the air conditioner 15 for the next period of time (e.g. to increase the comfort default value to be achieved) when it is predicted that the load of the air conditioner 15 will increase greatly, thereby achieving the purpose of saving power and avoiding extra peak power consumption. Moreover, when it is predicted that the load of the air conditioner 15 will decrease greatly, the next load of the air conditioner 15 may also be adjusted in advance (for example, the comfort level default value to be achieved is decreased), so that the comfort level of the indoor environment is further improved on the premise that the electric quantity or the stored ice amount is sufficient, and the air conditioner 15 and/or the ice water host machine can maintain the optimal operation efficiency of 60% to 80%.

Fig. 5 is a flowchart illustrating a modification process of an air conditioning apparatus according to a first embodiment of the present invention. Fig. 5 is a diagram for further describing how the central monitoring computer 14 adjusts the operation of the air conditioner 15 in real time in step S30 of fig. 4.

As shown in fig. 5, in the case where the air conditioner 15 is normally operated, the central monitoring computer 14 continuously monitors the operation of the air conditioner 15 and calculates the actual load amount of the air conditioner 15, and compares the predicted load amount calculated in advance with the actual load amount acquired in real time (step S300). Specifically, in step S300, the central monitoring computer 14 compares the current load capacity (i.e., the actual load capacity) of the air conditioner 15 with the load capacity (i.e., the predicted load capacity) in a future period of time (e.g., three hours).

Through the comparison in step S300, the central monitoring computer 14 may predict whether the air conditioner 15 will have a drastic change in load amount in a future period of time. For example, the central monitoring computer 14 compares the actual load amount at the current time (e.g., 12 pm) with the predicted load amount at a specific time (e.g., 3 pm), and finds that the load amount at the air conditioner 15 at the specific time may be greatly increased (e.g., a conference of many people is going to be opened) after the comparison. In this case, the central monitoring computer 14 can adjust the operation of the air conditioning equipment 15 in advance to maintain the comfort level of the indoor environment within a certain range, so that discomfort of indoor personnel due to drastic changes of the environment is avoided, and the purpose of saving power is achieved.

After step S300, if the central monitoring computer 14 determines that the predicted load (at the specific time point) is higher than the current actual load, the indoor comfort level default value that the air conditioner 15 needs to reach at the second time is adjusted in advance (step S302), and the temperature setting value and the wind speed setting value adopted by the air conditioner 15 are corrected according to the adjusted indoor comfort level default value. In this embodiment, since the central monitoring computer 14 is to increase the indoor comfort level default value (i.e. to decrease the comfort level of the indoor environment), the central monitoring computer 14 mainly increases the temperature setting value and decreases the wind speed setting value (step S304).

It is worth mentioning that the default value of the indoor comfort level in the present invention mainly adopts a Predicted Mean Volume (PMV) commonly used in the air conditioning field. When the indoor comfort level default value is 0, the comfort level of the current environment is moderate, the larger the indoor comfort level default value (+1, +2, +3) is, the hotter the current environment is represented, and when the indoor comfort level default value is smaller (-1, -2, -3), the colder the current environment is represented. Generally, the most comfortable range for human body is from-0.5 to + 0.5.

As can be seen from the above description, when the central monitoring computer 14 adjusts the indoor comfort level default value, the overall comfort level will be decreased (i.e. the indoor environment will be heated), so the load of the air conditioner 15 can be decreased. On the contrary, if the central monitoring computer 14 lowers the indoor comfort level default value, the overall comfort level will be lowered (i.e. the indoor environment will be cooled), and therefore the load of the air conditioning equipment 15 will be heavy.

If the central monitoring computer 14 determines in step S300 that the predicted load amount is lower than the actual load amount, it indicates that the air conditioner 15 has a space capable of increasing the load amount in the next period of time (for example, 1 to 3 hours in the future), so that the default indoor comfort level required to be reached by the air conditioner 15 at the second time can be adjusted in advance (step S306).

After step S306, the central monitoring computer 14 corrects the temperature setting value and the wind speed setting value of the air conditioning equipment 15 according to the adjusted and lowered indoor comfort level default value. In this embodiment, since the central monitoring computer 14 is to decrease the indoor comfort level default value (i.e. increase the comfort level of the indoor environment), the central monitoring computer 14 mainly decreases the temperature setting value and increases the wind speed setting value (step S308).

It is worth mentioning that generally, the overall comfort level of the indoor environment can be changed relatively quickly by modifying the temperature setting of the air conditioner 15, while the overall comfort level of the indoor environment can only be fine-tuned to a limited extent by modifying the wind speed setting of the air conditioner 15. Therefore, in step S308, the central monitoring computer 14 can also set the weight of the temperature setting value and the wind speed setting value. If the weight of the temperature setting value is higher than the weight of the wind speed setting value, the overall comfort level of the indoor environment can be adjusted relatively quickly after step S308, but the load of the air conditioning equipment 15 is relatively large. On the contrary, if the weight of the wind speed setting value is higher than the weight of the temperature setting value, after step S308, the improvement speed of the overall comfort of the indoor environment is slow, but the load of the air conditioner 15 is small. In other words, the user can set the above weights according to the actual purpose.

Through the technical scheme, the indoor comfort level of the air conditioning equipment 15 at the present stage can be corrected in real time by predicting the load capacity of the air conditioning equipment 15 for a period of time in the future, so that the aims of saving energy and reducing peak power consumption can be effectively achieved.

Specifically, the central monitoring computer 14 corrects the temperature setting value and the wind speed setting value adopted by the air conditioner 15 in advance according to the indoor comfort level default value, so that the severe operation adjustment of the air conditioner 15 due to the severe change of the environment can be avoided, and further discomfort of indoor personnel can be avoided. Furthermore, since the air conditioner 15 corrects the temperature and the wind speed in advance, the ice water main unit of the air conditioner 15 can be adjusted in a gradual manner to maintain the optimum operating efficiency range of 60% to 80%, thereby achieving the purpose of energy saving.

Fig. 6 is a flowchart illustrating a modification process of an air conditioning apparatus according to a second embodiment of the present invention. Fig. 6 is used to more specifically describe step S30 of fig. 4 described above.

As shown in fig. 6, the central monitoring computer 14 continuously monitors the actual load capacity of the air conditioner 15 (for example, by sensing with a sensor, or calculating by using the currently used temperature setting value and the wind speed setting value), and compares the predicted load capacity calculated in advance with the actual load capacity obtained in real time (step S320).

As described above, the predicted load amount in the present invention is the predicted load amount that the air conditioner 15 may need to be burdened in the future time interval. In step S320, the central monitoring computer 14 mainly compares the predicted load amount at a specific time (for example, after three hours) in the future with the current actual load amount of the air conditioner 15.

If the central monitoring computer 14 determines in step S320 that the predicted load at the future specific time is higher than the actual load, the central monitoring computer 14 further determines whether the ice storage capacity of the ice water main machine of the air conditioning system 1 is lower than the expected capacity by more than a specific percentage at the future specific time (step S322), for example, whether the ice storage capacity is lower than the expected capacity by more than 30% at the future three hours.

If the determination in step S322 is yes, it means that the air conditioner 15 will encounter a severe load change, so the central monitoring computer 14 can first greatly increase the indoor comfort level default value that the air conditioner 15 needs to reach at the second time (step S324). On the contrary, if the determination in step S322 is negative, it represents that the load change of the air conditioner 15 in the future specific time is small, so that the central monitoring computer 14 only slightly increases the default indoor comfort level value that the air conditioner 15 needs to reach at the second time (step S326).

In one embodiment, the central monitoring computer 14 sets the indoor comfort level default value +1 in step S324, and sets the indoor comfort level default value +0.5 in step S326, but not limited thereto.

Further, if the central monitoring computer 14 determines in step S320 that the predicted load amount in the future specific time will be lower than the actual load amount, the central monitoring computer 14 further determines whether the ice storage amount of the ice water main machine of the air conditioning system 1 is higher than the expected amount by more than a specific percentage in the future specific time (step S330), for example, whether the ice storage amount is higher than the expected amount by more than 30% in the future three hours.

If the determination in step S330 is yes, it indicates that the load of the air conditioner 15 in the future specific time is greatly improved (i.e., the power consumption is greatly reduced), so the central monitoring computer 14 can first greatly reduce the indoor comfort level default value that the air conditioner 15 needs to reach at the second time (step S332). On the contrary, if the determination in step S330 is negative, it means that the load of the air conditioner 15 in the future specific time is only slightly improved (i.e., the power consumption is slightly reduced), so that the central monitoring computer 14 only slightly reduces the indoor comfort level default value that the air conditioner 15 needs to reach at the second time (step S334).

In one embodiment, the central monitoring computer 14 sets the indoor comfort level to a default value of-1 in step S332, and sets the indoor comfort level to a default value of-0.5 in step S334, but not limited thereto.

After step S324, step S326, step S332 or step S334, the central monitoring computer 14 may then modify the temperature setting and the wind speed setting of the air conditioning equipment 15 according to the adjusted indoor comfort level default value (step S328). Specifically, the central monitoring computer 14 increases the temperature setting value and decreases the wind speed setting value according to the indoor comfort level default value adjusted in step S324 or S326. In addition, the central monitoring computer 14 decreases the temperature setting value and increases the wind speed setting value according to the decreased indoor comfort level default value in step S332 or step S334.

Through the technical scheme of the invention, the power consumption of the air conditioning equipment 15 in the power consumption peak time period (such as working time) can be effectively reduced, and the aims of energy conservation and optimal control are further fulfilled.

Please refer to fig. 7, which is a flowchart illustrating a predicted load calculation process according to a first embodiment of the present invention. Fig. 7 is a diagram for explaining how the air conditioning system 1 calculates the predicted load amount that the air conditioning equipment 15 may be loaded in the future time interval by the air conditioning load prediction unit 11.

As shown in fig. 7, before the air-conditioning equipment 15 is operated, the air-conditioning load prediction unit 11 of the adjustment system 1 obtains the schedule parameter of the air-conditioning equipment 15 in the past time interval (for example, yesterday' S working hour) through the air-conditioning system schedule management module 111 (step S100). For example, the air conditioner 1 may be configured with one or more Fan Control Units (FCUs) and one or more total Heat exchangers (HRVs) in a building. In this embodiment, the schedule parameter is a time schedule (such as on-time, wind speed, off-time, etc.) of the fan control units and the total heat exchanger in a past time interval.

The air conditioning load prediction unit 11 additionally calculates the indoor temperature setting conditions of the building in the past time zone by the indoor temperature setting module 112 (step S102). Specifically, the indoor temperature setting module 112 calculates the indoor temperature setting condition based on the indoor temperature and the outdoor temperature of the building in the past time interval. In one embodiment, the calculation formula of the indoor temperature setting condition is: t is_set＝0.48T_in+0.14T_out+8.22. Wherein, T_setSetting conditions for indoor temperature, T_inFor the room temperature of the building in the past time interval, T_outThe outdoor temperature of the building over the past time interval.

The air conditioning load prediction unit 11 also calculates the shell load factor of the building in the past time interval through the building shell load collection module 113 (step S104). For example, the building shell load collection module 113 may calculate the shell load factor of the building over the past time interval via E22 energy simulation software. The E22 energy simulation software is an open authorized public software, and is not described herein.

Specifically, the building shell load collection module 113 mainly collects the information of the material, landmark, and the like of the building into the E22 energy simulation software, respectively, to establish the shell information of the building. Then, the building shell load collection module 113 further imports the weather file around the place where the building is located into the E22 energy simulation software, and imports the parameters of the building windowing frequency, the building window shading factor, the building azimuth data and the like in the past time interval into the E22 energy simulation software, thereby calculating the shell load factor of the building.

The air conditioning load prediction unit 11 also obtains weather forecast data of the future time interval (e.g., the working hours of tomorrow) at the place where the building is located through the weather forecast data acquisition module 114 (step S106). In this embodiment, the weather forecast data may be, for example, the hourly outside air temperature and relative humidity of the building in the future time interval.

It should be noted that there is no fixed execution sequence from the step S100 to the step S106, and the air conditioning load prediction unit 11 may obtain the plurality of data respectively or simultaneously according to any sequence, without being limited to the sequence of steps shown in fig. 7.

After obtaining the schedule parameter, the indoor temperature setting condition, the shell load factor and the weather forecast data, the air conditioning load prediction module 115 may calculate the air conditioning load that the air conditioning equipment 15 may need to bear in the future time interval according to the schedule parameter, the indoor temperature setting condition, the shell load factor and the weather forecast data, and generate the predicted load amount (step S108).

Please refer to fig. 8, which shows a flowchart of the predicted load calculation according to the second embodiment of the present invention. Fig. 8 is used to describe step S108 of fig. 7 in detail, and further illustrates how the air conditioning load prediction module 115 of the present invention predicts the load amount that the air conditioning equipment 15 may need to bear in the future time interval.

As shown in fig. 8, the air conditioning load prediction module 115 first obtains the scheduling parameters, the indoor temperature setting conditions, the shell load factor and the weather forecast data (step S1080), so as to execute the corresponding prediction procedure according to these data.

In this embodiment, the air conditioning load prediction module 115 first calculates the corresponding external air enthalpy value according to the weather forecast data (step S1082).

In step S1082, the air conditioning load prediction module 115 calculates the atmospheric partial pressure in the future time interval according to the following formula one:

P_s＝(6.1164*10^{(7.591386*T/(T+240.7263)})/10；

formula one

In the above formula one, P_sThe predicted value of the atmospheric partial pressure in the future time interval and T are the hourly outside air temperature in the weather forecast data.

The air conditioning load prediction module 115 also calculates a humidity ratio in the future time interval according to the following equation two:

ω＝(0.6219*P_S*RH/100)/(101.325-(P_S*RH/100))；

formula two

In the second formula, ω is the predicted value of the humidity ratio in the future time interval, and RH is the relative humidity in the weather forecast data.

The air conditioning load prediction module 115 further calculates the outside air enthalpy value in the future time interval according to the following formula three:

H_oa＝T*(1.01+1.89*W)+2500*ω；

formula three

In the above formula III, H_oaIs a predicted value of the outside air enthalpy (kJ/kg) in the future time interval.

In this embodiment, the air conditioning load prediction module 115 first calculates the atmospheric partial pressure in the future time interval according to the time-by-time outside air temperature in the weather forecast data, then calculates the humidity ratio in the future time interval according to the atmospheric partial pressure and the relative humidity in the weather forecast data, and finally calculates the outside air enthalpy value in the future time interval according to the humidity ratio and the time-by-time outside air temperature in the weather forecast data.

After step S1082, the air conditioning load prediction module 115 further calculates the indoor enthalpy of the building in the past time interval according to the indoor temperature setting condition (step S1084). In this embodiment, the air conditioning load prediction module 115 mainly calculates the atmospheric partial pressure in the past time interval according to the following formula four:

P_s＝(6.1164*10^{(7.591386*T/(T+240.7263))})/10；

formula four

In the above formula four, P_ST is an atmospheric partial pressure in the past time interval, and T is the indoor temperature setting condition.

The air conditioning load prediction module 115 also calculates the humidity ratio in the past time interval according to the following equation five:

ω＝(0.6219*P_s*65/100)/(101.325-(P_s*65/100))；

formula five

In the fifth equation, the humidity ratio in the past time interval is shown.

The air conditioning load prediction module 115 also calculates the indoor enthalpy value in the past time interval according to the following formula six:

H_indoor＝T*(1.01+1.89*W)+2500*ω；

formula six

In the above formula six, H_indoorIs the indoor enthalpy value in the past time interval. In this embodiment, the air conditioning load prediction module 115 first calculates the atmospheric pressure in the past time interval according to the indoor temperature setting condition, then calculates the humidity ratio in the past time interval according to the atmospheric pressure and the preset humidity value, and finally calculates the indoor enthalpy value according to the humidity ratio and the indoor temperature setting condition.

After step S1084, the air conditioning load prediction module 115 further calculates an outside air introduction load according to the scheduling parameters and the calculated outside air enthalpy value (step S1086), where the outside air introduction load refers to a hot air that may be added to the building due to the active introduction of outside air (e.g., performing indoor and outdoor air exchange). In other words, the step S1086 predicts the possible actions performed by the building in the future time interval, and calculates the hot air that may be added to the building due to the execution of the actions, i.e. the load that may be added to the air conditioner 15 in the future time interval.

Specifically, the air conditioning load prediction module 115 may calculate the outside air introduction load mainly according to the following formula seven:

η*ρ*m*(H_oa-40.13)/3600*T_open；

formula seven

In the seventh formula, η is the equipment efficiency (%) of the air conditioner 15, and ρ is the air density (kg/m)³) M is the air volume (CMH), H_oaFor calculating the resulting outside air enthalpy value, T_openIs a scheduling parameter of the air conditioner 15. It is worth mentioning that the above η may be a standard equipment efficiency indicated on the cabinet of the air conditioning equipment 15, and ρ may be a standard air density, i.e., 1.2 (kg/m)³) But is not limited thereto.

After step S1086, the air conditioning load prediction module 115 further calculates an indoor enthalpy difference according to the outdoor enthalpy and the indoor enthalpy (step S1088). Specifically, the air conditioning load prediction module 115 may calculate the difference between the indoor enthalpy and the outdoor enthalpy according to the following equation eight:

H_oa-H_indoor；

equation eight

Next, the air conditioning load prediction module 115 calculates an air conditioning load that the air conditioning equipment 15 may need to bear in a future time interval according to the outside air introduction load, the indoor-outdoor enthalpy difference, and the enclosure load factor, and generates a corresponding predicted load amount (step S1090).

In this embodiment, the air conditioning load prediction module 115 mainly calculates the predicted load capacity according to the external air introduction load, the difference between the indoor and outdoor enthalpies, and a plurality of shell load factors respectively representing different orientations (e.g., east, west, south, and north) of the building, so that the problem of inaccurate prediction due to only considering sensible heat when a general air conditioning system predicts future load can be solved.

The adjusting system 1 of the present invention can predict the load that the air conditioning device 15 may need to bear in the future time interval (e.g. tomorrow) according to the data collected in the past time interval (e.g. yesterday), and correct the temperature setting value and the wind speed setting value of the air conditioning device 15 in real time by comparing the actual load with the predicted load one by one when the air conditioning device 15 is operating, thereby effectively realizing the optimized control of the air conditioning device 15, and further achieving the purposes of saving energy and reducing power consumption in the peak time interval.

The above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention.

The present invention is capable of other embodiments, and various changes and modifications may be made by one skilled in the art without departing from the spirit and scope of the invention as defined in the appended claims.

Claims

1. An air conditioning load adjustment system for use in a building, comprising:

a central monitoring computer;

2. The system of claim 1, further comprising a black-bulb temperature sensing module for sensing and outputting a radiation temperature of the building at the first time, and the comfort prediction module calculates the indoor comfort default according to the sensed temperature, the sensed humidity, the air-conditioning wind speed, and the radiation temperature.

3. The system of claim 2, wherein the indoor comfort level prediction module obtains a human activity meter and a clothing meter, and calculates the indoor comfort level default value according to the sensed temperature, the sensed humidity, the air conditioning wind speed, the radiation temperature, the human activity meter and the clothing meter.

4. The system of claim 3, wherein the indoor comfort prediction module stores a plurality of human activity meters corresponding to different locations, and reads the corresponding human activity meters according to the property of the building.

5. The system of claim 3, wherein the indoor comfort prediction module stores a plurality of clothing meters corresponding to different climates, and reads the corresponding clothing meters according to the outdoor temperature of the building.

6. The system of claim 3, wherein the indoor comfort prediction module stores a plurality of clothing meters corresponding to different climates, and reads the corresponding clothing meter according to a current season.

7. The system of claim 3, wherein the energy management platform is configured to raise the default indoor comfort level that the air conditioning equipment needs to reach at the second time when the predicted load is higher than the actual load for a future period of time.

8. The system of claim 7, wherein the central monitoring computer increases the temperature setting and decreases the wind speed setting according to the adjusted indoor comfort level default.

9. The system of claim 3, wherein the energy management platform decreases the default indoor comfort level required by the air conditioning equipment at the second time when the predicted load is lower than the actual load for a future period of time.

10. The system of claim 9, wherein the central monitoring computer decreases the temperature setting and increases the wind speed setting according to the decreased indoor comfort level default.

11. The air conditioning load adjustment system according to claim 3, wherein the air conditioning load prediction unit includes:

12. The system of claim 11, wherein the weather forecast data includes an outside air temperature and a relative humidity for the future time interval.

13. The system of claim 11, wherein the building envelope load module calculates the envelope load factor based on a building windowing frequency, a building window shading factor, and at least one building orientation data of the building during the past time interval.

14. The system of claim 11, wherein the air conditioning load prediction module calculates an outdoor enthalpy value according to the weather forecast data, calculates an indoor enthalpy value according to the indoor temperature setting condition, calculates an indoor and outdoor enthalpy difference value according to the outdoor enthalpy value and the indoor enthalpy value, calculates an outdoor air intake load according to the scheduling parameter and the outdoor enthalpy value, and calculates the predicted load capacity according to the outdoor air intake load, the indoor and outdoor enthalpy difference value, and the enclosure load factor.

15. An air conditioning load adjusting method applied to a building and controlling an air conditioning device in the building, comprising the steps of:

16. An air conditioner load adjusting method according to claim 15, further comprising a step d1) before the step d): sensing a radiation temperature of the building at the first time through a black ball temperature sensing module;

17. An air conditioner load adjusting method according to claim 16, further comprising a step d2) before the step d): obtaining a human activity scale and a clothing scale;

18. The method as claimed in claim 17, wherein the indoor comfort prediction module stores a plurality of physical activity meters corresponding to different locations, and the step d2) reads the corresponding physical activity meters according to the property of the building.

19. The air conditioning load adjusting method according to claim 17, wherein the indoor comfort prediction module stores a plurality of clothing meters corresponding to different climates, and the step d2) reads the corresponding clothing meter according to the outdoor temperature of the building.

20. The air conditioning load adjusting method according to claim 17, wherein the indoor comfort prediction module stores a plurality of clothing meters corresponding to different climates, and the step d2) reads the corresponding clothing meters according to the current season.

21. The air conditioning load adjusting method according to claim 17, wherein the step g) comprises the steps of:

22. The air conditioning load adjusting method according to claim 17, wherein the step g) comprises the steps of:

23. The air conditioning load adjusting method according to claim 17, wherein the step a) comprises the steps of:

24. The method of claim 23, wherein the weather forecast data includes an outside air temperature and a relative humidity of the future time interval.

25. The method of claim 23, wherein the building shell load collection module calculates the shell load factor according to a building windowing frequency, a building window shading factor and at least one building orientation data of the building in the past time interval.

26. The method of claim 23, wherein the step a5) comprises calculating an outdoor enthalpy according to the weather forecast data, calculating an indoor enthalpy according to the indoor temperature setting condition, calculating an indoor/outdoor enthalpy difference according to the outdoor enthalpy and the indoor enthalpy, calculating an outdoor air intake load according to the schedule parameters and the outdoor enthalpy, and calculating the predicted load capacity according to the outdoor air intake load, the indoor/outdoor enthalpy difference and the casing load factor.